ShiftTree: An Interpretable Model-Based Approach for Time Series Classification. - Balázs Hidasi; Csaba Gáspár-Papanek (ECML/PKDD (2), 2011)

Enhancing matrix factorization through initialization for implicit feedback databases. - Balázs Hidasi; Domonkos Tikk (CaRR, 2012)

Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback. - Balázs Hidasi; Domonkos Tikk (ECML/PKDD (2), 2012)

Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback. - Dávid Zibriczky; Balázs Hidasi; Zoltán Petres; Domonkos Tikk (UMAP Workshops, 2012)

Context-aware item-to-item recommendation within the factorization framework. - Balázs Hidasi; Domonkos Tikk (CaRR@WSDM, 2013)

Context-aware recommendations from implicit data via scalable tensor factorization. - Balázs Hidasi; Domonkos Tikk (CoRR, 2013)

Initializing Matrix Factorization Methods on Implicit Feedback Databases. - Balázs Hidasi; Domonkos Tikk (J. Univers. Comput. Sci., 2013)

Approximate modeling of continuous context in factorization algorithms. - Balázs Hidasi; Domonkos Tikk (CaRR@ECIR, 2014)

Using Interaction Signals for Job Recommendations. - Benjamin Kille; Fabian Abel; Balázs Hidasi; Sahin Albayrak (MobiCASE, 2015)

Context-aware Preference Modeling with Factorization. - Balázs Hidasi (RecSys, 2015)

Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations. - Balázs Hidasi; Massimo Quadrana; Alexandros Karatzoglou; Domonkos Tikk (RecSys, 2016)

RecSys'16 Workshop on Deep Learning for Recommender Systems (DLRS). - Alexandros Karatzoglou; Balázs Hidasi; Domonkos Tikk; Oren Sar Shalom; Haggai Roitman; Bracha Shapira; Lior Rokach (RecSys, 2016)

The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems. - Roberto Pagano; Paolo Cremonesi; Martha A. Larson; Balázs Hidasi; Domonkos Tikk; Alexandros Karatzoglou; Massimo Quadrana (RecSys, 2016)

Theano: A Python framework for fast computation of mathematical expressions. - Rami Al-Rfou; Guillaume Alain; Amjad Almahairi; Christof Angermüller; Dzmitry Bahdanau; Nicolas Ballas; Frédéric Bastien; Justin Bayer; Anatoly Belikov; Alexander Belopolsky; Yoshua Bengio; Arnaud Bergeron; et al. (CoRR, 2016)

Session-based Recommendations with Recurrent Neural Networks. - Balázs Hidasi; Alexandros Karatzoglou; Linas Baltrunas; Domonkos Tikk (ICLR (Poster), 2016)

General factorization framework for context-aware recommendations. - Balázs Hidasi; Domonkos Tikk (Data Min. Knowl. Discov., 2016)

Speeding up ALS learning via approximate methods for context-aware recommendations. - Balázs Hidasi; Domonkos Tikk (Knowl. Inf. Syst., 2016)

Context-aware factorization methods for implicit feedback based recommendation problems - Balázs Hidasi (2016)

DLRS 2017: Second Workshop on Deep Learning for Recommender Systems. - Balázs Hidasi; Alexandros Karatzoglou; Oren Sar Shalom; Sander Dieleman; Bracha Shapira; Domonkos Tikk (RecSys, 2017)

Deep Learning for Recommender Systems. - Alexandros Karatzoglou; Balázs Hidasi (RecSys, 2017)

Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. - Massimo Quadrana; Alexandros Karatzoglou; Balázs Hidasi; Paolo Cremonesi (RecSys, 2017)

Cutting-Edge Collaborative Recommendation Algorithms: Deep Learning. - Balázs Hidasi (Collaborative Recommendations, 2018)

Recurrent Neural Networks with Top-k Gains for Session-based Recommendations. - Balázs Hidasi; Alexandros Karatzoglou (CIKM, 2018)

Multimedia recommender systems. - Yashar Deldjoo; Markus Schedl; Balázs Hidasi; Peter Knees (RecSys, 2018)

DLRS 2018: third workshop on deep learning for recommender systems. - Balázs Hidasi; Alexandros Karatzoglou; Oren Sar Shalom; Bracha Shapira; Domonkos Tikk; Flavian Vasile; Sander Dieleman (RecSys, 2018)

IEEE Access Special Section Editorial: Social Computing Applications for Smart Cities. - Cristina Rottondi; Giacomo Verticale; Piero Fraternali; Jasminko Novak; Konstantinos Pelechrinis; Balázs Hidasi; Carmen Karina Vaca Ruiz (IEEE Access, 2019)

Multimedia Recommender Systems: Algorithms and Challenges. - Yashar Deldjoo; Markus Schedl; Balázs Hidasi; Yinwei Wei; Xiangnan He 001 (Recommender Systems Handbook, 2022)

The Effect of Third Party Implementations on Reproducibility. - Balázs Hidasi; Ádám Tibor Czapp (RecSys, 2023)

Widespread Flaws in Offline Evaluation of Recommender Systems. - Balázs Hidasi; Ádám Tibor Czapp (RecSys, 2023)

Dynamic Product Image Generation and Recommendation at Scale for Personalized E-commerce. - Ádám Tibor Czapp; Mátyás Jani; Bálint Domián; Balázs Hidasi (RecSys, 2024)